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xiaoshen-transactions-analysis
分析和总结小申的消费习惯和消费倾向,基于交易记录数据生成分类统计和占比分析。
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分析和总结小申的消费习惯和消费倾向,基于交易记录数据生成分类统计和占比分析。
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Multi search engine integration with 4 engines: Google, DuckDuckGo, Brave Search, and WolframAlpha. Supports advanced search operators, time filters, and knowledge queries. No API keys required.
Generate and edit images with gpt-image-2 through a unified Python raw-HTTP CLI. Use when Codex needs OpenAI-compatible image generation, image-to-image editing, /v1/images/generations, /v1/images/edits, optional /v1/responses image_generation tool support, fixed in-script API key/base URL defaults, retry handling, and reproducible request/response JSON artifacts.
Generate images through the custom OpenAI-compatible Responses endpoint at https://codex.ciii.club/v1/responses using top-level model gpt-5.4 and the image_generation tool with gpt-image-2. Use when Codex needs a deterministic Python CLI workflow, explicit request and response JSON artifacts, or the user explicitly asks to use this endpoint/API path instead of the built-in image tool.
Generate images through the custom OpenAI-compatible Responses endpoint at https://codex.ciii.club/v1/responses using top-level model gpt-5.4 and the image_generation tool with gpt-image-2. Prefer the bundled OpenAI SDK workflow for deterministic Python CLI generation with explicit request and response JSON artifacts; fall back to the raw HTTP script only when the SDK path is unavailable or the user explicitly asks for it instead of the built-in image tool.
UI/UX design intelligence. 67 styles, 96 palettes, 57 font pairings, 25 charts, 13 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, mobile app, .html, .tsx, .vue, .svelte. Elements: button, modal, navbar, sidebar, card, table, form, chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, flat design. Topics: color palette, accessibility, animation, layout, typography, font pairing, spacing, hover, shadow, gradient. Integrations: shadcn/ui MCP for component search and examples.
Guide for creating effective skills. Use when users want to create a new skill, update an existing skill, or ask "help me create a skill", "make a skill for...", "I want to build a skill". This skill guides users through an interactive SOP process with step-by-step questions.
Based on SOC occupation classification
| name | xiaoshen-transactions-analysis |
| description | 分析和总结小申的消费习惯和消费倾向,基于交易记录数据生成分类统计和占比分析。 |
| tags | ["finance","analysis","transactions","consumption"] |
| version | 1.0.0 |
| author | CodeBuddy |
| allowed-tools | null |
| disable | false |
此SKILL用于分析和总结小申的消费习惯和消费倾向,基于交易记录数据生成分类统计和占比分析。
该SKILL通过调用MCP服务获取指定周期内的消费数据,对消费进行分类统计,并输出基于百分比的汇总结果,可渲染为表格形式。
get_transactions_by_user MCP服务获取消费记录yyyy)或按月(yyyy-mm)查询get_transactions_by_user
获取指定用户的消费记录数据
| 参数名 | 类型 | 说明 | 示例值 |
|---|---|---|---|
user_id | string | 用户ID | "user123" |
period | string | 查询周期,支持年或年月格式 | "2025" 或 "2025-01" |
MCP服务返回交易记录数组,每条记录包含以下字段:
[
{
"account_id": 2,
"amount": "14.00",
"date": "2025-12-31",
"desc": "专二",
"from_account_id": null,
"id": 11203,
"item": "咖啡",
"opposite_trans_id": null,
"to_account_id": null,
"type": -1
},
{
"account_id": 1,
"amount": "34.93",
"date": "2025-12-31",
"desc": "都城",
"from_account_id": null,
"id": 11204,
"item": "餐饮",
"opposite_trans_id": null,
"to_account_id": null,
"type": -1
}
]
item: 消费项目类别,用于分类统计amount: 交易金额(字符串格式)date: 交易日期desc: 交易描述type: 交易类型(负数表示支出)account_id: 账户ID检查是否已获取必要的MCP参数:
user_id: 用户标识period: 查询周期当用户未提供足够的MCP参数时,按以下优先级询问:
优先级1: user_id
优先级2: period
询问示例:
item 字段分组输出包含以下内容的汇总报告:
=== 消费汇总分析(2025-01)===
消费类别 | 金额(元) | 占比
--------------|----------|--------
餐饮 | 34.93 | 71.4%
咖啡 | 14.00 | 28.6%
总支出: 48.93 元
记录数: 2 条
amount 字段为字符串格式,需转换为数值进行计算yyyy 和 yyyy-mm 两种周期格式可在实现中添加: